ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19
Ali H. Abbasa, Sheryl Ann Abdukahilb, Nurul Najmee Abdulkadirc, Ryuzo Abed, Laurent Abele, Lara Absilf, Kamal Abu Jabalg, Hiba Zayyadg, Subhash Acharyah, Andrew M. Ackeri, Shingo Adachij, Elisabeth Adam
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Abstract
The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use. Measurement(s) CDISC SDTM Vital Sign Test Name Terminology Technology Type(s) CDISC Define-XML General Observation Class Terminology Factor Type(s) Hospital Mortality • COVID-19 Sample Characteristic - Organism Homo sapiens Sample Characteristic - Environment hospital Measurement(s) CDISC SDTM Vital Sign Test Name Terminology Technology Type(s) CDISC Define-XML General Observation Class Terminology Factor Type(s) Hospital Mortality • COVID-19 Sample Characteristic - Organism Homo sapiens Sample Characteristic - Environment hospital
TL;DRThe International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with CO VID-19, and its characteristics are presented. (Semantic Scholar)

